As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crud...As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.展开更多
针对混合关键级系统中的固定优先级任务节能问题,文中提出了基于概率性分析的混合关键级系统节能调度算法。混合关键级系统的实时性要求使得系统建模和分析偏向于较坏的情况。该类系统中出现任务超限的情况相对较少,易存在资源配置过度...针对混合关键级系统中的固定优先级任务节能问题,文中提出了基于概率性分析的混合关键级系统节能调度算法。混合关键级系统的实时性要求使得系统建模和分析偏向于较坏的情况。该类系统中出现任务超限的情况相对较少,易存在资源配置过度问题。通过DVFS(Dynamic Voltage Frequency Scaling)技术和混合关键级系统调度算法相结合的方式挖掘空闲时间,从而在保证系统实时性的前提下降低系统的能耗。利用MCSIMU仿真软件对所提算法进行了仿真验证,实验结果表明,对于固定优先级任务与未使用节能调度算法相比,固定优先级节能调度算法的节能率可达45%。展开更多
基金This work was financially supported by the National Natural Science Foundation of China(52074089 and 52104064)Natural Science Foundation of Heilongjiang Province of China(LH2019E019).
文摘As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.
文摘针对混合关键级系统中的固定优先级任务节能问题,文中提出了基于概率性分析的混合关键级系统节能调度算法。混合关键级系统的实时性要求使得系统建模和分析偏向于较坏的情况。该类系统中出现任务超限的情况相对较少,易存在资源配置过度问题。通过DVFS(Dynamic Voltage Frequency Scaling)技术和混合关键级系统调度算法相结合的方式挖掘空闲时间,从而在保证系统实时性的前提下降低系统的能耗。利用MCSIMU仿真软件对所提算法进行了仿真验证,实验结果表明,对于固定优先级任务与未使用节能调度算法相比,固定优先级节能调度算法的节能率可达45%。